Learn Claude — Part 4: Files, Vision & Real Data Analysis
Typed prompts only scratch the surface. Claude's practical power multiplies when you feed it your material — documents, screenshots, spreadsheets — and this is where the hallucination problem from Part 1 gets its most important fix.
Grounding: why files change everything
When Claude answers from training data, it's recalling — and recall can be wrong. When Claude answers from a document in its context window, it's reading. Answers become checkable against a source you both share. Professionals exploit this constantly:
Instead of "What does GDPR say about data retention?" (recall, hallucination-prone) upload the actual regulation and ask "According to this document, what are the data-retention rules? Quote the relevant sections." (reading, verifiable)
The instruction "answer only from the document, and say if it's not covered" is one of the most valuable sentences in this series.
Documents: the core workflows
Drag any file into the chat — PDFs, Word docs, text, code. The moves that matter:
Targeted extraction: "List every deadline, penalty, and obligation in this contract as a table."
Guided summary: "Summarize this 60-page report for someone deciding whether to fund the project." A summary's audience changes what belongs in it — always state one.
Interrogation: "What does this lease say about early termination? Quote it." Follow-ups are free; the file stays in context.
Cross-document work: upload two versions and ask "What changed between these, and which changes shift risk to me?" Multi-file comparison is something humans are slow at and Claude is fast at.
Transformation: meeting notes → action-item email; research paper → blog outline; requirements doc → test checklist.
Vision: Claude can genuinely see
Uploaded images aren't decorations — Claude analyzes them:
Screenshot of an error → "Diagnose and fix." (Often faster than copying the text.)
Whiteboard photo → "Turn this into structured notes with action items."
A chart → "What's the trend, and what's misleading about how this is presented?"
UI screenshot → "Critique this design for usability."
Handwriting, foreign-language forms → transcribe, translate, explain each field.
One built-in boundary: Claude won't identify real people in photos.
The professional layer: executed data analysis
Here's the distinction that separates casual use from real analysis. From Part 1: Claude's mental arithmetic is unreliable. The fix is built in — the analysis tool / code execution (enable it in Settings if needed). When it's relevant, Claude writes actual code, runs it on your file, and reports the computed results.
Upload a CSV and try:
"Compute monthly revenue growth and flag anomalies. Use code, show your work."
"Clean this data: trim whitespace, standardize dates, list duplicates — then give me the cleaned file."
"Which two columns correlate most strongly? Plot it."
The output is the difference between "revenue seems to grow around 10%" (estimated, maybe hallucinated) and "revenue grew 11.4% month-over-month" (computed). When numbers matter, the magic phrase is "use code to calculate this."
Knowing the limits
Size ceilings exist. Very large files can exceed the context window. Strategies: split by chapter, or summarize sections in separate chats and synthesize the summaries (context distillation again, from Part 2).
Long-document attention. In huge documents, details buried mid-file get less attention than the start and end. For contracts and compliance work, ask section-targeted questions rather than one giant "check everything."
Scanned PDFs vary. Claude handles them, but low-quality scans degrade extraction — spot-check quotes against the page.
Verification discipline stays. Grounding shrinks hallucination; it doesn't abolish it. For consequential documents, verify quoted passages exist. The habit costs a minute.
A realistic workflow: competitor research
Upload three competitor pricing PDFs → "Extract all plans and prices into one comparison table."
"Use code: compute the average price per feature tier."
"Which competitor changed positioning compared to this older PDF?" (upload it)
End with distillation: "Summarize the strategic picture in 10 bullets" → carry that into a fresh chat for strategy work.
Four prompts. That used to be an afternoon.
Exercise
Take a real spreadsheet or export (bank statement, sales data, anything). Ask one question without code, then the same question with "use code to calculate this." Compare the answers — this lesson sticks best when you see the difference yourself.
Next up
Part 5: Artifacts — turning conversations into working documents, tools, and apps you can actually ship.
